Source: Technology Review
One of the characteristics of our increasingly information-driven lives is the huge amounts of data being generated about everything from sporting activities and Twitter comments to genetic patterns and disease predictions. These information firehoses are generally known as “big data,” and with them come the grand challenge of making sense of the material they produce.
That’s no small task. The Twitter stream alone produces some 500 million tweets a day. This has to be filtered, analyzed for interesting trends, and then displayed in a way that humans can make sense of quickly.
It is this last task of data display that Zachary Weber and Vijay Gadepally have taken on at MIT’s Lincoln Laboratory in Lexington, Massachusetts. They say that combining big data with 3-D printing can dramatically improve the way people consume and understand data on a massive scale.
They make their argument using the example of a 3-D printed model of the MIT campus, which they created using a laser ranging device to measure the buildings. They used this data to build a 3-D model of the campus which they printed out in translucent plastic using standard 3-D printing techniques.
One advantage of the translucent plastic is that it can be illuminated from beneath with different colors. Indeed, the team used a projector connected to a laptop computer to beam an image on the model from below. The image above shows the campus colored according to the height of the buildings.
But that’s only the beginning of what they say is possible. To demonstrate, Weber and Gadepally filtered a portion of the Twitter stream to pick out tweets that were geolocated at the MIT campus. They can then use their model to show what kind of content is being generated in different locations on the campus and allow users to cut and dice the data using an interactive screen. “Other demonstrations may include animating twitter traffic volume as a function of time and space to provide insight into campus patterns or life,” they say.
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